Aufgaben:Exercise 4.5: Pseudo Noise Modulation: Difference between revisions

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{{quiz-Header|Buchseite=Examples_of_Communication_Systems/Telecommunications_Aspects_of_UMTS}}
{{quiz-Header|Buchseite=Examples_of_Communication_Systems/Telecommunications_Aspects_of_UMTS}}


[[File:EN_Bei_A_4_5.png|right|frame|Equivalent circuit of PN modulation and BPSK]]
[[File:EN_Bei_A_4_5.png|right|frame|Models of PN modulation (top) and BPSK (bottom)]]
The graph above shows the equivalent circuit of "pseudo-noise" modulation  (''Direct Sequence Spread Spectrum'', abbreviated  '''DS-SS''')  in the equivalent low-pass region. $n(t)$  denotes AWGN noise.
The upper diagram shows the equivalent circuit of  $\rm PN$  modulation  $($Direct-Sequence Spread Spectrum, abbreviated  $\rm DS–SS)$  in the equivalent low-pass range,  based on AWGN noise  $n(t)$.   


Below is sketched the low pass model of  [[Modulation_Methods/Linear_Digital_Modulation#BPSK_.E2.80.93_Binary_Phase_Shift_Keying|"Binary Phase Shift Keying"]].
Shown below is the low-pass model of binary phase shift keying  $\rm (BPSK)$. 
*The low-pass transmit signal  $s(t)$  is set equal to the rectangular source signal  $q(t) ∈ \{+1, -1\}$  with rectangular duration  $T$  only for reasons of uniform representation.
*The low-pass transmitted signal  $s(t)$  is set equal to the rectangular source signal  $q(t) ∈ \{+1, –1\}$  with rectangular duration  $T$  for reasons of uniformity.
*The integrator function can be written as follows:
:$$d (\nu T) = \frac{1}{T} \cdot \hspace{0.03cm} \int_{(\nu -1 )T }^{\nu T} \hspace{-0.3cm} b (t )\hspace{0.1cm} {\rm d}t \hspace{0.05cm}.$$
*The two models differ by multiplication by the  $±1$-spread signal  $c(t)$  at the transmitter and receiver, where only the degree of spread  $J$  is known from  $c(t)$ .
*For the solution of this exercise, the specification of the specific spreading sequence  (M sequence or Walsh function)  is not important.


*The function of the integrator can be described as follows:
:$$d (\nu T) = \frac{1}{T} \cdot \hspace{-0.1cm} \int_{(\nu -1 )T }^{\nu T} \hspace{-0.3cm} b (t )\hspace{0.1cm} {\rm d}t \hspace{0.05cm}.$$


What needs to be investigated is whether the lower BPSK model can also be applied in PN modulation and whether the BPSK error probability
*The two models differ by multiplication with the  $±1$  spreading signal  $c(t)$  at transmitter and receiver,  where only the spreading factor  $J$  is known from  $c(t)$. 
:$$p_{\rm B} = {\rm Q} \left( \hspace{-0.05cm} \sqrt { {2 \cdot E_{\rm B}}/{N_{\rm 0}} } \hspace{-0.05cm} \right )$$
is also valid for PN modulation, or how to modify the given equation.




It has to be investigated whether the lower BPSK model can also be used for PN modulation and whether the BPSK error probability
:$$p_{\rm B} = {\rm Q} \left( \hspace{-0.05cm} \sqrt { {2 \cdot E_{\rm B}}/{N_{\rm 0}} } \hspace{0.05cm} \right )$$
is also valid for PN modulation,  or how the given equation should be modified.




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Notes:
*This exercise mostly refers to the page  [[Examples_of_Communication_Systems/Telecommunications_Aspects_of_UMTS|"Telecommunications Aspects of UMTS"]].


 
*For the solution of this exercise,  the specification of the specific spreading sequence  $($M-sequence or Walsh function$)$  is not important.
 
 
Hints:
 
*This exercise belongs to the chapter  [[Examples_of_Communication_Systems/Telecommunications_Aspects_of_UMTS|"Telecommunications Aspects of UMTS"]].
*The CDMA method used in UMTS also goes by the name "PN modulation".
*The nomenclature used in this exercise is partly based on the chapter  [[Modulation_Methods/Direct-Sequence_Spread_Spectrum_Modulation|"PN Modulation"]]  in the book "Modulation Methods".




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<quiz display=simple>
<quiz display=simple>
 
{Which detection signal values are possible with BPSK&nbsp; (in the noise-free case)?
{What detection signal values are possible with BPSK in the noise-free case?
|type="[]"}
|type="[]"}
- $d(\nu T)$&nbsp; is Gaussian distributed.
- $d(νT)$&nbsp; can be Gaussian distributed.
- $d(\nu T)$&nbsp; can take the values&nbsp; $+1, \ 0$&nbsp; and&nbsp; $-1$&nbsp;.
- $d(νT)$&nbsp; can take the values &nbsp;$+1$, &nbsp;$0$&nbsp; and &nbsp;$-1$.&nbsp;
+ Only the values&nbsp; $d(\nu T) = +1$&nbsp; and&nbsp; $d(\nu T) = -1$&nbsp; are possible.
+ Only the values &nbsp;$d(νT) = +1$&nbsp; and &nbsp;$d(νT) = -1$&nbsp; are possible.


{What values are possible with PN modulation in the noise-free case?
{Which values are possible in PN modulation&nbsp; (in the noise-free)&nbsp; case?
|type="[]"}
|type="[]"}
- $d(\nu T)$&nbsp; is Gaussian distributed.
- $d(νT)$&nbsp; can be Gaussian distributed.
- $d(\nu T)$&nbsp; can take the values&nbsp; $+1, \ 0$&nbsp; and&nbsp; $-1$&nbsp;.
- $d(νT)$&nbsp; can take the values &nbsp;$+1$, &nbsp;$0$&nbsp; and &nbsp;$-1$.&nbsp;
+ Only the values&nbsp; $d(\nu T) = +1$&nbsp; and&nbsp; $d(\nu T) = -1$&nbsp; are possible.
+ Only the values &nbsp;$d(νT) = +1$&nbsp; and &nbsp;$d(νT) = -1$&nbsp; are possible.


{What modification must be made to the BPSK model to make it applicable to PN modulation?
{What modification must be made to the BPSK model to make it applicable to PN modulation?
|type="[]"}
|type="[]"}
+ The noise&nbsp; $n(t)$&nbsp; must be replaced by&nbsp; $n\hspace{0.05cm}'(t) = n(t) \cdot c(t)$&nbsp;.
+ The noise &nbsp;$n(t)$&nbsp; must be replaced by &nbsp;$n'(t) = n(t) · c(t)$.&nbsp;  
- The integration must now be done over&nbsp; $J \cdot T$&nbsp; .
- The integration must now be done over &nbsp;$J · T$.&nbsp;
- The noise power must be reduced by a factor of&nbsp; $J$&nbsp;.
- The noise power &nbsp;$σ_n^2$&nbsp; must be reduced by a factor of &nbsp;$J$.&nbsp;  


{What is the bit error probability&nbsp; $p_{\rm B}$&nbsp; for&nbsp; $10 \cdot {\rm lg} \ (E_{\rm B}/N_{0}) = 6 \ \rm dB$&nbsp; for PN modulation? <br>''Note:'' &nbsp; For BPSK, in this case: &nbsp; $p_{\rm B} \approx 2.3 \cdot 10^{-3}$.
{What is the bit error probability &nbsp;$p_{\rm B}$&nbsp; for &nbsp;$10 \lg \ (E_{\rm B}/N_0) = 6\ \rm dB$&nbsp; for PN modulation?&nbsp; <br>Note: &nbsp; For BPSK, the following applies in this case: &nbsp; $p_{\rm B} 2.3 · 10^{–3}$.
|type="()"}
|type="()"}
- The larger&nbsp; $J$&nbsp; is chosen, the smaller&nbsp; $p_{\rm B}$ is.
- The larger &nbsp;$J$&nbsp; is chosen, the smaller &nbsp;$p_{\rm B}$ is.
- The larger&nbsp; $J$&nbsp; is chosen, the larger&nbsp; $p_{\rm B}$.
- The larger &nbsp;$J$&nbsp; is chosen, the larger &nbsp;$p_{\rm B}$ is.
+ It always results in the value&nbsp; $2.3 \cdot 10^{-3}$ regardless of&nbsp; $J$&nbsp;.
+ Independent of &nbsp;$J$,&nbsp; the value &nbsp;$p_{\rm B} ≈ 2.3 · 10^{–3}$ is always obtained.
</quiz>
</quiz>


===Solution===
===Solution===
{{ML-Kopf}}
{{ML-Kopf}}
'''(1)'''&nbsp; The&nbsp; <u>last solution</u>&nbsp; is correct:
*We are dealing here with an optimal receiver.
*Without noise,&nbsp; the signal&nbsp; $b(t)$&nbsp; within each bit is constantly equal to&nbsp; $+1$&nbsp; or&nbsp; $-1$.
*From the given equation for the integrator
:$$d (\nu T) = \frac{1}{T} \cdot \hspace{-0.1cm} \int_{(\nu -1 )T }^{\nu T} \hspace{-0.3cm} b (t )\hspace{0.1cm} {\rm d}t $$
:it follows that&nbsp; $d(νT)$&nbsp; can take only the values&nbsp; $+1$&nbsp; and&nbsp; $-1$.&nbsp;


'''(1)'''&nbsp; Correct is the <u>last proposed solution</u>:
*This is an optimal receiver.
*Without noise, signal&nbsp; $b(t)$&nbsp; within each bit is constant equal to $+1$ or $-1$.
*From the given equation for the integrator, it follows that&nbsp; $d(\nu T)$&nbsp; can only take the values $±1$:
:$$d (\nu T) = \frac{1}{T} \cdot \hspace{-0.1cm} \int_{(\nu -1 )T }^{\nu T} \hspace{-0.3cm} b (t )\hspace{0.1cm} {\rm d}t.$$




 
'''(2)'''&nbsp; Again the&nbsp; <u>last solution</u>&nbsp; is correct:
'''(2)'''&nbsp; Correct again is the <u>last proposed solution</u>:  
* In the noise&ndash; and interference-free case &nbsp; &nbsp; $n(t) = 0$,&nbsp; the twofold multiplication by&nbsp; $c(t) ∈ \{+1, –1\}$&nbsp; can be omitted,
*In the noise-free case &nbsp; &rArr; &nbsp; $n(t) = 0$, the twofold multiplication with&nbsp; $c(t) ∈ \{+1, -1\} \ \Rightarrow \ c(t)^{2} = 1$&nbsp; can be omitted,  
*so that the upper model is identical to the lower model.
*so that the upper model is identical to the lower model.






'''(3)'''&nbsp; Only the <u>proposed solution 1</u> is applicable:
'''(3)'''&nbsp; <u>Solution 1</u>&nbsp; is correct:
*Since both models are identical in the noise-free case, only the noise signal needs to be adjusted: &nbsp; $n\hspace{0.05cm}'(t) = n(t) \cdot c(t)$.  
*Since both models are identical in the noise-free case,&nbsp; only the noise signal has to be adjusted: &nbsp; $n'(t) = n(t) · c(t)$.  
*Suggestions 2 and 3, on the other hand, are not applicable: &nbsp; Integration must still be done over&nbsp; $T = J \cdot T_{\rm c}$&nbsp; and PN modulation does not reduce AWGN noise.  
*In contrast,&nbsp; the other two solutions are not applicable:
 
*The integration must still be done over&nbsp; $T = J · T_c$&nbsp; and the PN modulation does not reduce the AWGN noise.




'''(4)'''&nbsp; Correct is the <u>last proposed solution</u>:
*Multiplying the AWGN noise by the high frequency&nbsp; $±1$ signal&nbsp; $c(t)$, the noise is also Gaussian and white.
*Because&nbsp; $E[c^{2}(t)] = 1$&nbsp; the noise variance is also not changed. The equation valid for BPSK
:$$p_{\rm B} = {\rm Q} \left( \hspace{-0.05cm} \sqrt { {2 \cdot E_{\rm B}}/{N_{\rm 0}} } \hspace{-0.05cm} \right )$$
:is thus also applicable to PN&ndash;modulation and is independent of the spreading factor&nbsp; $J$&nbsp; and of the specific spreading sequence.


:&nbsp; &rArr; &nbsp; '''Thus, in the case of AWGN noise, the error probability is neither increased nor decreased by band spreading'''.  
'''(4)'''&nbsp; The&nbsp; <u>last solution</u>&nbsp; is correct:
*Multiplying the AWGN noise by the high-frequency&nbsp; $±1$ signal&nbsp; $c(t)$,&nbsp; the product is also Gaussian and white.
*Because of &nbsp;${\rm E}\big[c^2(t)\big] = 1$,&nbsp; the noise variance is not changed either.&nbsp; Thus:                                                           
*The equation&nbsp; $p_{\rm B} = {\rm Q} \left( \hspace{-0.05cm} \sqrt {{2 E_{\rm B}}/{N_{\rm 0}} } \hspace{0.05cm} \right )$&nbsp; valid for BPSK is also applicable for PN modulation,&nbsp; independent of spreading factor&nbsp; $J$&nbsp; and specific spreading sequence.
*Ergo:&nbsp; For AWGN noise,&nbsp; band spreading neither increases nor decreases the error probability.
{{ML-Fuß}}
{{ML-Fuß}}






[[Category:Examples of Communication Systems: Exercises|^4.3 Telecommunications Aspects
[[Category:Modulation Methods: Exercises|^5.2 PN Modulation^]]
 
 
^]]

Revision as of 18:47, 4 March 2023

Models of PN modulation (top) and BPSK (bottom)

The upper diagram shows the equivalent circuit of  $\rm PN$  modulation  $($Direct-Sequence Spread Spectrum, abbreviated  $\rm DS–SS)$  in the equivalent low-pass range,  based on AWGN noise  $n(t)$. 

Shown below is the low-pass model of binary phase shift keying  $\rm (BPSK)$. 

  • The low-pass transmitted signal  $s(t)$  is set equal to the rectangular source signal  $q(t) ∈ \{+1, –1\}$  with rectangular duration  $T$  for reasons of uniformity.
  • The function of the integrator can be described as follows:
$$d (\nu T) = \frac{1}{T} \cdot \hspace{-0.1cm} \int_{(\nu -1 )T }^{\nu T} \hspace{-0.3cm} b (t )\hspace{0.1cm} {\rm d}t \hspace{0.05cm}.$$
  • The two models differ by multiplication with the  $±1$  spreading signal  $c(t)$  at transmitter and receiver,  where only the spreading factor  $J$  is known from  $c(t)$. 


It has to be investigated whether the lower BPSK model can also be used for PN modulation and whether the BPSK error probability

$$p_{\rm B} = {\rm Q} \left( \hspace{-0.05cm} \sqrt { {2 \cdot E_{\rm B}}/{N_{\rm 0}} } \hspace{0.05cm} \right )$$

is also valid for PN modulation,  or how the given equation should be modified.



Notes:

  • For the solution of this exercise,  the specification of the specific spreading sequence  $($M-sequence or Walsh function$)$  is not important.


Questions

1 Which detection signal values are possible with BPSK  (in the noise-free case)?

$d(νT)$  can be Gaussian distributed.
$d(νT)$  can take the values  $+1$,  $0$  and  $-1$. 
Only the values  $d(νT) = +1$  and  $d(νT) = -1$  are possible.

2 Which values are possible in PN modulation  (in the noise-free)  case?

$d(νT)$  can be Gaussian distributed.
$d(νT)$  can take the values  $+1$,  $0$  and  $-1$. 
Only the values  $d(νT) = +1$  and  $d(νT) = -1$  are possible.

3 What modification must be made to the BPSK model to make it applicable to PN modulation?

The noise  $n(t)$  must be replaced by  $n'(t) = n(t) · c(t)$. 
The integration must now be done over  $J · T$. 
The noise power  $σ_n^2$  must be reduced by a factor of  $J$. 

4 What is the bit error probability  $p_{\rm B}$  for  $10 \lg \ (E_{\rm B}/N_0) = 6\ \rm dB$  for PN modulation? 
Note:   For BPSK, the following applies in this case:   $p_{\rm B} ≈ 2.3 · 10^{–3}$.

The larger  $J$  is chosen, the smaller  $p_{\rm B}$ is.
The larger  $J$  is chosen, the larger  $p_{\rm B}$ is.
Independent of  $J$,  the value  $p_{\rm B} ≈ 2.3 · 10^{–3}$ is always obtained.


Solution

(1)  The  last solution  is correct:

  • We are dealing here with an optimal receiver.
  • Without noise,  the signal  $b(t)$  within each bit is constantly equal to  $+1$  or  $-1$.
  • From the given equation for the integrator
$$d (\nu T) = \frac{1}{T} \cdot \hspace{-0.1cm} \int_{(\nu -1 )T }^{\nu T} \hspace{-0.3cm} b (t )\hspace{0.1cm} {\rm d}t $$
it follows that  $d(νT)$  can take only the values  $+1$  and  $-1$. 


(2)  Again the  last solution  is correct:

  • In the noise– and interference-free case   ⇒   $n(t) = 0$,  the twofold multiplication by  $c(t) ∈ \{+1, –1\}$  can be omitted,
  • so that the upper model is identical to the lower model.


(3)  Solution 1  is correct:

  • Since both models are identical in the noise-free case,  only the noise signal has to be adjusted:   $n'(t) = n(t) · c(t)$.
  • In contrast,  the other two solutions are not applicable:
  • The integration must still be done over  $T = J · T_c$  and the PN modulation does not reduce the AWGN noise.


(4)  The  last solution  is correct:

  • Multiplying the AWGN noise by the high-frequency  $±1$ signal  $c(t)$,  the product is also Gaussian and white.
  • Because of  ${\rm E}\big[c^2(t)\big] = 1$,  the noise variance is not changed either.  Thus:
  • The equation  $p_{\rm B} = {\rm Q} \left( \hspace{-0.05cm} \sqrt {{2 E_{\rm B}}/{N_{\rm 0}} } \hspace{0.05cm} \right )$  valid for BPSK is also applicable for PN modulation,  independent of spreading factor  $J$  and specific spreading sequence.
  • Ergo:  For AWGN noise,  band spreading neither increases nor decreases the error probability.